{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a plot with some random data points\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9af9a7b9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(-10,10,20)\n",
    "y = np.sin(x)\n",
    "plt.plot(x,y, marker='*', linestyle='', color=\"red\", markersize=20)\n",
    "plt.plot(x,-y, marker='s', linestyle='', color=\"green\", markersize=10)\n",
    "plt.savefig(\"images/markers.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from skimage.feature import blob_log\n",
    "from skimage.color import rgb2gray\n",
    "from skimage.io import imread"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "img = imread(\"images/markers.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(288, 432, 4)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f9af872ec50>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9af8785470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "star_bounding_box = [(179,226),(214,251)]\n",
    "cropped = img[star_bounding_box[0][1]:star_bounding_box[1][1], star_bounding_box[0][0]:star_bounding_box[0][1], :]\n",
    "plt.imshow(cropped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: calculate these based on selection above:\n",
    "fg_color = (255, 0, 0, 0)\n",
    "fg_distance = 200\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [],
   "source": [
    "gray_img = np.zeros((img.shape[0],img.shape[1]))\n",
    "for y in range(0, img.shape[0]):\n",
    "    for x in range(0, img.shape[1]):\n",
    "        dist = (img[y, x, :] - fg_color)[0:3]\n",
    "        dist = np.sqrt(dist[0]*dist[0] + dist[1]*dist[1] + dist[2]*dist[2])\n",
    "        if dist < fg_distance:\n",
    "            gray_img[y,x] = 255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(288, 432)"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gray_img.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f9af3658b00>"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9af3a8ab00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(gray_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [],
   "source": [
    "blobs = blob_log(gray_img, max_sigma=20, min_sigma=16, threshold=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 3)"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blobs.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9af3d529e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(10,10))\n",
    "ax.imshow(img)\n",
    "for blob in blobs:\n",
    "    x, y, r = blob\n",
    "    c = plt.Circle((y, x), r, color=\"orange\", fill=False)\n",
    "    ax.add_patch(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
